Estimating treatment effects with treatment switching via semicompeting risks models: an application to a colorectal cancer study

DOI10.1093/BIOMET/ASR062zbMath1437.62669OpenAlexW1985867206WikidataQ36142974 ScholiaQ36142974MaRDI QIDQ3224224

Amgen Research Group, Donglin Zeng, Qingxia Chen, Joseph G. Ibrahim, Ming-Hui Chen

Publication date: 29 March 2012

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3412606

zbMATH Keywords

noncompliance expectation-maximization algorithm maximum likelihood estimate transition model partial switching panitumumab

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50) Estimation in survival analysis and censored data (62N02)

Related Items (9)

A Bayesian multi‐risks survival (MRS) model in the presence of double censorings ⋮ Estimation of complier causal treatment effects with informatively interval-censored failure time data ⋮ Estimation of complier causal treatment effects under the case–cohort studies with interval-censored failure time data ⋮ A Semi‐parametric Transformation Frailty Model for Semi‐competing Risks Survival Data ⋮ Estimation of treatment effects and model diagnostics with two-way time-varying treatment switching: an application to a head and neck study ⋮ Bayesian path specific frailty models for multi-state survival data with applications ⋮ Bayesian gamma frailty models for survival data with semi-competing risks and treatment switching ⋮ Quantifying the average of the time-varying hazard ratio via a class of transformations ⋮ Using Inverse Probability Weighting Estimators to Evaluate Various Propensity Scores When Treatment Switching Exists

This page was built for publication: Estimating treatment effects with treatment switching via semicompeting risks models: an application to a colorectal cancer study